DocumentCode
42412
Title
Advances in Probabilistic Modeling: Applications of Stochastic Geometry [From the Guest Editors]
Author
Adams, Martin ; Vo, Ba-Ngu ; Mahler, Ronald
Author_Institution
Professor of Electrical Engineering, Universidad de Chile, Santiago, 837-0451, Chile
Volume
21
Issue
2
fYear
2014
fDate
Jun-14
Firstpage
21
Lastpage
24
Abstract
The articles in this special section advocate that the same principle applies to feature detection and autonomous mapping in robotics, where, instead of referring to the problem of target estimation, the problem of map feature or environmental object estimation are of concern. From here on, map features, targets, and environmental objects of interest will simply be referred to as ???features.??? In the case of robotic mapping and SLAM, realistic feature detection algorithms produce false alarms and missed detections, and estimating the true number of map features is, therefore, central to these problems.
Keywords
Estimation; Feature extraction; Geometry; Modeling; Probabilistic logic; Simultaneous localization and mapping; Special issues and sections; Stochastic systems; Terrain mapping;
fLanguage
English
Journal_Title
Robotics & Automation Magazine, IEEE
Publisher
ieee
ISSN
1070-9932
Type
jour
DOI
10.1109/MRA.2014.2314018
Filename
6827353
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